Biology subjects

Ross, J. V.

Publications and source records attributed to Ross, J. V..

5 recordsLinked to original sources

bioRxiv2022

Leveraging a natural murine meiotic drive to suppress invasive populations

Invasive rodents, including house mice, are a major cause of environmental damage and biodiversity loss, particularly in island ecosystems. Eradication can be achieved through the distribution of rodenticide, but this approach is expensive to apply at scale, can have negative impacts (e.g. on non-target species, or through contamination), has animal ethics concerns, and has restrictions on where it can be used. Gene drives, which exhibit biased inheritance, have been proposed as a next generation strategy to control invasive alien pests and disease vectors. However, synthetic gene drives including CRISPR homing drives have proven to be technically challenging to develop in mice. The t haplotype is a naturally-occurring segregation distortion locus with highly biased transmission from heterozygous males. Here we propose a novel gene drive strategy for population suppression, tCRISPR, that leverages t haplotype bias and an embedded SpCas9/gRNA transgene to spread inactivating mutations in a haplosufficient female fertility gene. Using spatially explicit individual-based in silico modelling, we show that polyandry, sperm competition, dispersal, and transmission bias are critical factors for tCRISPR-mediated population suppression. Modelling of realistic parameter values indicates that tCRISPR can eradicate an island population of 200,000 mice while the unmodified t haplotype fails under the same conditions. We also demonstrate feasibility of this approach by engineering tCRISPR mice in a safe split drive format. tCRISPR mice exhibit high transmission of the modified t haplotype, and efficient generation and transmission of inactivating mutations in a recessive female fertility gene, crucially, at levels for which the modelling predicts that population eradication can occur. This is the first example of a feasible gene drive system for invasive alien rodent population control.

genetics↗

bioRxiv2019

Bayesian model discrimination for partially-observed epidemic models

An efficient method for Bayesian model selection is presented for a broad class of continuous-time Markov chain models and is subsequently applied to two important problems in epidemiology. The first problem is to identify the shape of the infectious period distribution; the second problem is to determine whether individuals display symptoms before, at the same time, or after they become infectious. In both cases we show that the correct model can be identified, in the majority of cases, from symptom onset data generated from multiple outbreaks in small populations. The method works by evaluating the likelihood using a particle filter that incorporates a novel importance sampling algorithm designed for partially-observed continuous-time Markov chains. This is combined with another importance sampling method to unbiasedly estimate the model evidence. These come with estimates of precision, which allow for stopping criterion to be employed. Our method is general and can be applied to a wide range of model selection problems in biological and epidemiological systems with intractable likelihood functions.

epidemiology↗

bioRxiv2019

Identification of the relative timing of infectiousness and symptom onset for outbreak control

In an outbreak of an emerging disease the epidemiological characteristics of the pathogen may be largely unknown. A key determinant of ability to control the outbreak is the relative timing of infectiousness and symptom onset. We provide a method for identifying this relationship with high accuracy based on data from household-stratified symptom-onset data. Further, this can be achieved with observations taken on only a few specific days, chosen optimally, within each household. This constitutes an important tool for outbreak response. An accurate and computationally-efficient heuristic for determining the optimal surveillance scheme is introduced. This heuristic provides a novel approach to optimal design for Bayesian model discrimination.

epidemiology↗

bioRxiv2019

Locally Fixed Alleles: A method to localize gene drive to island populations

Invasive species pose a major threat to biodiversity on islands. While successes have been achieved using traditional removal methods, such as toxicants aimed at rodents, these approaches have limitations and various off-target effects on island ecosystems. Gene drive technologies designed to eliminate a population provide an alternative approach, but the potential for drive-bearing individuals to escape from the target release area and impact populations elsewhere is a major concern. Here we propose the \"Locally Fixed Alleles\" approach as a novel means for localizing elimination by a drive to an island population that exhibits significant genetic isolation from neighboring populations. Our approach is based on the assumption that in small island populations of rodents, genetic drift will lead to multiple genomic alleles becoming fixed. In contrast, multiple alleles are likely to be maintained in larger populations on mainlands. Utilizing the high degree of genetic specificity achievable using homing drives, for example based on the CRISPR/Cas9 system, our approach aims at employing one or more locally fixed alleles as the target for a gene drive on a particular island. Using mathematical modeling, we explore the feasibility of this approach and the degree of localization that can be achieved. We show that across a wide range of parameter values, escape of the drive to a neighboring population in which the target allele is not fixed will at most lead to modest transient suppression of the non-target population. While the main focus of this paper is on elimination of a rodent pest from an island, we also discuss the utility of the locally fixed allele approach for the goals of population suppression or population replacement. Our analysis also provides a threshold condition for the ability of a gene drive to invade a partially resistant population.

evolutionary biology↗

bioRxiv2018

Connecting surveillance and population-level influenza incidence

There is substantial interest in estimating and forecasting influenza incidence. Surveillance of influenza is challenging as one needs to demarcate influenza from other respiratory viruses, and due to asymptomatic infections. To circumvent these challenges, surveillance data often targets influenza-like-illness, or uses context-specific normalisations such as test positivity or per-consultation rates. Specifically, influenza incidence itself is not reported. We propose a framework to estimate population-level influenza incidence, and its associated uncertainty, using surveillance data and hierarchical observation processes. This new framework, and forecasting and forecast assessment methods, are demonstrated for three Australian states over 2016 and 2017. The framework allows for comparison within and between seasons in which surveillance effort has varied. Implementing this framework would improve influenza surveillance and forecasting globally, and could be applied to other diseases for which surveillance is difficult.

epidemiology↗